Facial Emoji Avatars generation based on face emotion

Abstract

Face expressions are an intrinsic aspect of
nonverbal communication and play a significant role
in Human Computer Interaction. The formation of
facial emoticons is a human-computer interaction
device. Emoji generation in real time based on a
person's facial expression hasalways been difficult.
Human social conversations depend on facial
expressions. Since the world is becoming more
technologically sophisticated day in day out, there
are more interactive encounters, such as text
messages, than physical ones. Emoticons promote
virtual social interaction by reducing the amount of
words exchanged. This paper describes an Emoji
generation methodology based on Facial Expression
Recognition (FER) and Convolutional Neural
Networks (CNN) coupled with Machine Learning
and Deep Learning. This CNN-based model can be
put to work to evaluate feelings as users watch movie
trailers or video lessons, as well as to help people with
autism regulate their emotions